Yea it was meant to be a vague question.  I just wanted to see what some of
the answers were.  It's for a project for school.  We've done k nearest
neighbors, principal component analysis, partial least squares, and we'll
prob throw a random forest in there too.

Thanks

On Wed, May 30, 2012 at 10:24 PM, Peter Langfelder <
peter.langfelder@gmail.com> wrote:

> On Wed, May 30, 2012 at 4:07 PM, Chris Burns <chris.burns2@gmail.com>
> wrote:
> > I have a huge matrix of unspecified covariates and the corresponding
> sales
> > for them.  What is the best way to predict the sales from the covariates?
> >
>
> Don't want to sound rude, but given your very vague problem
> specifications, the best way seems to be to consult a local
> statistician or machine learning specialist. You can also look up
> literature on prediction or machine learning, in particular predictors
> like k nearest neighbors, Random Forest, Support Vector Machines etc.
> Once you decide which predictor(s) to test and use, finding a good R
> implementation will be trivial.
>
> HTH,
>
> Peter
>

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